{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6cde7c61",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96172d31",
   "metadata": {},
   "outputs": [],
   "source": [
    "INPUT_FILE = Path(\"raw_data.tsv\")\n",
    "OUTPUT_FILE = Path(\"clean_data.csv\")\n",
    "\n",
    "assert INPUT_FILE.exists()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9260f649",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_input = pd.read_csv(INPUT_FILE, sep=\"\\t\", header=None)\n",
    "df_input.columns = [\"class\", \"text\"]\n",
    "df_input[\"class\"] = df_input[\"class\"].map({\"ham\": 0, \"spam\": 1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3758aff2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove duplicates\n",
    "\n",
    "print(\"Rows before dropping duplicates:\", len(df_input))\n",
    "df_input = df_input.drop_duplicates(subset=[\"text\"])\n",
    "print(\"Rows after dropping duplicates:\", len(df_input))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f25f3e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an 80/20 train/test split\n",
    "\n",
    "train_idx, test_idx = train_test_split(df_input.index, test_size=0.2, random_state=42, stratify=df_input[\"class\"])\n",
    "df_input[\"is_train\"] = 0\n",
    "df_input.loc[train_idx, \"is_train\"] = 1\n",
    "df_input = df_input[[\"is_train\", \"class\", \"text\"]].sort_values(by=\"is_train\")\n",
    "\n",
    "print(\"Train set size:\", (df_input[\"is_train\"] == 1).sum())\n",
    "print(\"Test set size:\", (df_input[\"is_train\"] == 0).sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2bcf7cf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_input[[\"is_train\", \"class\", \"text\"]].to_csv(OUTPUT_FILE, index=False)"
   ]
  }
 ],
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